{"id":"https://openalex.org/W7134036340","doi":"https://doi.org/10.48550/arxiv.2603.04745","title":"Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset","display_name":"Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134036340","doi":"https://doi.org/10.48550/arxiv.2603.04745"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.04745","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128243144","display_name":"Yang Zou","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zou, Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128267579","display_name":"Jun F\u00e9lix Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Jun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041238968","display_name":"Zhidong Jiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiao, Zhidong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128267311","display_name":"Xingyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xingyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128243148","display_name":"Zhiying Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhiying","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5121407279","display_name":"Jinyuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jinyuan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5128243144"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.5533999800682068,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.5533999800682068,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.2572000026702881,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.03830000013113022,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5342000126838684},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5303999781608582},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.4959999918937683},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4887999892234802},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48500001430511475},{"id":"https://openalex.org/keywords/thermal","display_name":"Thermal","score":0.44440001249313354},{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.4438000023365021},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.39570000767707825},{"id":"https://openalex.org/keywords/thermal-infrared","display_name":"Thermal infrared","score":0.3774999976158142}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6373000144958496},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5342000126838684},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5303999781608582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5011000037193298},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.4959999918937683},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4887999892234802},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48500001430511475},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.39570000767707825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38670000433921814},{"id":"https://openalex.org/C2984335091","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Thermal infrared","level":3,"score":0.3774999976158142},{"id":"https://openalex.org/C2779222261","wikidata":"https://www.wikidata.org/wiki/Q624587","display_name":"Thermography","level":3,"score":0.3702000081539154},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.367900013923645},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.36410000920295715},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.329800009727478},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C50637493","wikidata":"https://www.wikidata.org/wiki/Q1136781","display_name":"Morphing","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.26930001378059387},{"id":"https://openalex.org/C2776445388","wikidata":"https://www.wikidata.org/wiki/Q6716998","display_name":"MODTRAN","level":3,"score":0.26579999923706055},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25220000743865967}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.04745","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.04745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.04745","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.04745","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Infrared":[0],"image":[1],"super-resolution":[2],"(IISR)":[3],"under":[4,157],"real-world":[5,70,167,196],"conditions":[6],"is":[7],"a":[8,65,82,91,117,131,137,166,192],"practically":[9],"significant":[10],"yet":[11],"rarely":[12],"addressed":[13],"task.":[14],"Pioneering":[15],"works":[16],"are":[17,41,204],"often":[18],"trained":[19],"and":[20,32,46,55,78,105,142,160,180,198,202],"evaluated":[21],"on":[22,126],"simulated":[23],"datasets":[24],"or":[25],"neglect":[26],"the":[27,100,186],"intrinsic":[28],"differences":[29],"between":[30,102,140],"infrared":[31,39,173],"visible":[33],"imaging.":[34],"In":[35],"practice,":[36],"however,":[37],"real":[38],"images":[40,174],"affected":[42],"by":[43],"coupled":[44],"optical":[45],"sensing":[47],"degradations":[48,110],"that":[49,72,120],"jointly":[50],"deteriorate":[51],"both":[52],"structural":[53,106],"sharpness":[54],"thermal":[56,76,96,103,128,161],"fidelity.":[57],"To":[58],"address":[59],"these":[60],"challenges,":[61],"we":[62],"propose":[63],"Real-IISR,":[64,190],"unified":[66,193],"autoregressive":[67],"framework":[68],"for":[69,195],"IISR":[71,168,197],"progressively":[73],"reconstructs":[74],"fine-grained":[75],"structures":[77],"clear":[79],"backgrounds":[80],"in":[81],"scale-by-scale":[83],"manner":[84],"via":[85,176],"thermal-structural":[86],"guided":[87],"visual":[88],"autoregression.":[89],"Specifically,":[90],"Thermal-Structural":[92],"Guidance":[93],"module":[94],"encodes":[95],"priors":[97],"to":[98,153],"mitigate":[99],"mismatch":[101],"radiation":[104],"edges.":[107],"Since":[108],"non-uniform":[109],"typically":[111],"induce":[112],"quantization":[113],"bias,":[114],"Real-IISR":[115],"adopts":[116],"Condition-Adaptive":[118],"Codebook":[119],"dynamically":[121],"modulates":[122],"discrete":[123],"representations":[124],"based":[125],"degradation-aware":[127],"priors.":[129],"Also,":[130],"Thermal":[132],"Order":[133],"Consistency":[134],"Loss":[135],"enforces":[136],"monotonic":[138],"relation":[139],"temperature":[141],"pixel":[143],"intensity,":[144],"ensuring":[145],"relative":[146],"brightness":[147],"order":[148],"rather":[149],"than":[150],"absolute":[151],"values":[152],"maintain":[154],"physical":[155],"consistency":[156],"spatial":[158],"misalignment":[159],"drift.":[162],"We":[163],"build":[164],"FLIR-IISR,":[165],"dataset":[169,201],"with":[170],"paired":[171],"LR-HR":[172],"acquired":[175],"automated":[177],"focus":[178],"variation":[179],"motion-induced":[181],"blur.":[182],"Extensive":[183],"experiments":[184],"demonstrate":[185],"promising":[187],"performance":[188],"of":[189],"providing":[191],"foundation":[194],"benchmarking.":[199],"The":[200],"code":[203],"available":[205],"at:":[206],"https://github.com/JZD151/Real-IISR.":[207]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-07T00:00:00"}